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Experience building production systems with more modern ETL and data systems, such as AWS Glue, Databricks, Snowflake, Elastic, and Azure Cognitive Search. Implement data-related business logic on modern data platforms, such as AWS Glue, Databricks, Snowflake, Elastic, and Azure Cognitive Search using best practices and industry standards.
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Experience with SQL, Python, Data Warehousing, DBT, Airflow and Kafka. You have experience with Data Warehousing, Airflow, AWS, Kafka and dbt. At least 5+ years of data engineer and/or software development experience.
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Knowledge of Data Engineering and the respective tools and technologies (e.g., Apache Spark, Databricks, Python, SQL DB, Data Lake concepts) As a Data Engineer on the LAPA team, you will be responsible for designing and implementing data pipelines using industry-leading cloud applications such as Databricks and orchestration tools such as Azure Data Factory.
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Experience implementing solutions using at least one of the following technologies Azure Data Factory, Azure Event Hubs, Azure Data Lake Storage, Azure Function Apps, Azure Synapse Analytics, AWS Glue, AWS S3, AWS Lambda Functions, AWS Redshift, Databricks, Snowflake, Google Big Query, Alteryx, SSIS, Informatica.
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Requirements: Azure Data Factory, Azure Data Lake Storage, Python/ PySpark, SQL Database, Proficiency in written and spoken English Responsibilities: Develop and deploy data warehouse solution in Azure Cloud, Design and implement data ingestion to Azure Storage services, Creation of data transformations using Data Factory, Synapse Analytics, Databricks.
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Data visualization skills using business intelligence solutions including at least one of Looker, Tableau, Periscope, Pentaho, or Microstrategy. Fluency in at least one modern language useful for data processing (e.g. Python, Scala.
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Data Warehouse Skills: Proficient in Cloud Data Warehouse systems such as Redshift, Snowflake, or BigQuery. Coding Enthusiast: Comfortable with Python, Kotlin, and GoLang, and eager to explore new data technologies.
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Practical & recent experience in data pipeline development with Big Data frameworks (Databricks, Spark, Kafka), data modelling approaches (Star schema, Snowflake, Data Vault), and Azure Services (Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
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Experience in big data technologies(Apache Hadoop/Spark/Hive/Presto) Build and deploy scalable data engineering solutions on the cloud for engineering, analytics & data-science consumers.
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This team plays a pivotal role in managing all facets of data ingestion, storage, and transformation, leveraging modern tools and environments like Databricks, DBT, Airflow, Kubernetes, AWS, ThoughtSpot and Terraform.
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Familiarity with modern data tools such as BigQuery, Snowflake, Metabase, dbt or their equivalents. At least 2 years of experience in a data engineering, data science, or analyst role at a high-growth or early stage startup — or equivalent open-source/personal project work.
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Experience with cloud and big data technologies to extract and analyze data (Snowflake, S3, Redshift, Athena, Hive, BigQuery, Spark, etc). Realtor.com is seeking a Senior Economist on the Economics Research team with expertise in data-driven storytelling to a variety of audiences, strong analytic instincts, and skills to build models from large data.
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You’ll be an integral part of the organisation and expected todesign andsetting up well-functioning fully automated data platforms and data pipelines, as well as contributing to ways of working and product strategy.
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Banking industry, Insurance industry, Data Warehousing, Data modeling, Data mastering, Data quality, Informatica, Alteryx, MSSQL, Oracle, Teradata, Hadoop, Snowflake, MSSQL, SSIS, SSRS, Python, R, Scala, SPARK a další programovací jazyky, reporting.
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Experience with cloud solutions for Big Data (Snowflake, GCP BigQuery, AWS Redshift) Starting as a BI Developer working on Microsoft Stack-based data warehouses, now I am focusing on Azure Cloud Data services and Power BI as a Data Architect.
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